A time-to-live based reservation algorithm on fully decentralized resource discovery in Grid computing

  • Authors:
  • Sanya Tangpongprasit;Takahiro Katagiri;Kenji Kise;Hiroki Honda;Toshitsugu Yuba

  • Affiliations:
  • Graduate School of Information Systems, The University of Electro-Communications 1-5-1 Choufu-gaoka, Choufu-shi, Tokyo 182-8585, Japan;Graduate School of Information Systems, The University of Electro-Communications 1-5-1 Choufu-gaoka, Choufu-shi, Tokyo 182-8585, Japan;Graduate School of Information Systems, The University of Electro-Communications 1-5-1 Choufu-gaoka, Choufu-shi, Tokyo 182-8585, Japan;Graduate School of Information Systems, The University of Electro-Communications 1-5-1 Choufu-gaoka, Choufu-shi, Tokyo 182-8585, Japan;Graduate School of Information Systems, The University of Electro-Communications 1-5-1 Choufu-gaoka, Choufu-shi, Tokyo 182-8585, Japan

  • Venue:
  • Parallel Computing
  • Year:
  • 2005

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Abstract

We present an alternative algorithm of fully decentralized resource discovery in Grid computing, which enables the sharing, selection, and aggregation of a wide variety of geographically distributed computational resources. Our algorithm is based on a simply unicast request transmission that can be easily implemented. The addition of a reservation algorithm is enable resource discovery mechanism to find more available matching resources. The deadline for resource discovery time is decided with time-to-live value. With our algorithm, the only one resource is automatically decided for any request if multiple available resources are found on forward path of resource discovery, resulting in no need to ask user to manually select the resource from a large list of available matching resources. We evaluated the performance of our algorithms by comparing with first-found-first-served algorithm. The experiment results show that the percentages of request that can be supported by both algorithms are not different. However, it can improve the performance of either resource utilization or turnaround time, depending on how to select the resource. The algorithm that finds the available matching resource whose attributes are closest to the required attribute can improve the resource utilization, whereas another one that finds the available matching resource which has the highest performance can improve the turn-around time. However, it is found that the performance of our algorithm relies on the density of resource in the network. Our algorithm seems to perform well only in the environment with enough resources, comparing with the density of requests in the network.